Acccept word2vec formats too. #1875
Merged
Conversation
This file contains bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
|
Hello! I didn't realise about the difference in formats, but I was under the impression that word2vec was supported. For example: word_embedding_model = models.WordEmbeddings.from_text_file('GoogleNews-vectors-negative300.txt.gz')Do you have an example of a common file that doesn't currently work?
|
|
I've prepared a word2vec file via gensim and its |
tomaarsen
reviewed
Dec 18, 2023
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
Add this suggestion to a batch that can be applied as a single commit.
This suggestion is invalid because no changes were made to the code.
Suggestions cannot be applied while the pull request is closed.
Suggestions cannot be applied while viewing a subset of changes.
Only one suggestion per line can be applied in a batch.
Add this suggestion to a batch that can be applied as a single commit.
Applying suggestions on deleted lines is not supported.
You must change the existing code in this line in order to create a valid suggestion.
Outdated suggestions cannot be applied.
This suggestion has been applied or marked resolved.
Suggestions cannot be applied from pending reviews.
Suggestions cannot be applied on multi-line comments.
Suggestions cannot be applied while the pull request is queued to merge.
Suggestion cannot be applied right now. Please check back later.
The difference between word2vec and glove embeddings (in text format) is just that in word2vec the first line indicates the size of the vocabulary and the embeddings dimensions. With this commit, the line is ignored and WordEmbeddings class is now able to read embeddings in both formats.